DOI: 10.1175/JCLI-D-16-0429.1
Scopus记录号: 2-s2.0-85027247940
论文题名: Quantifying the dependence of satellite cloud retrievals on instrument uncertainty
作者: Shea Y.L. ; Wielicki B.A. ; Sun-Mack S. ; Minnis P.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期: 17 起始页码: 6959
结束页码: 6976
语种: 英语
Scopus关键词: Aerosols
; Atmospheric radiation
; Climate models
; Earth (planet)
; Optical properties
; Orbits
; Satellites
; Temperature
; Uncertainty analysis
; Climate record
; Climate variability
; Cloud retrieval
; Decadal variability
; Satellite observations
; Climate change
英文摘要: Cloud response to Earth's changing climate is one of the largest sources of uncertainty among global climate model (GCM) projections. Two of the largest sources of uncertainty are the spread in equilibrium climate sensitivity (ECS) and uncertainty in radiative forcing due to uncertainty in the aerosol indirect effect. Satellite instruments with sufficient accuracy and on-orbit stability to detect climate change-scale trends in cloud properties will improve confidence in the understanding of the relationship between observed climate change and cloud property trends, thus providing information to better constrain ECS and radiative forcing. This study applies a climate change uncertainty framework to quantify the impact of measurement uncertainty on trend detection times for cloud fraction, effective temperature, optical thickness, and water cloud effective radius. Although GCMs generally agree that the total cloud feedback is positive, disagreement remains on its magnitude. With the climate uncertainty framework, it is demonstrated how stringent measurement uncertainty requirements for reflected solar and infrared satellite measurements enable improved constraint of SW and LW cloud feedbacks and the ECS by significantly reducing trend uncertainties for cloud fraction, optical thickness, and effective temperature. The authors also demonstrate improved constraint on uncertainty in the aerosol indirect effect by reducing water cloud effective radius trend uncertainty. © 2017 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49893
Appears in Collections: 气候变化事实与影响
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作者单位: NASA Langley Research Center, Hampton, VA, United States; Science Systems and Applications, Inc., Hampton, VA, United States
Recommended Citation:
Shea Y.L.,Wielicki B.A.,Sun-Mack S.,et al. Quantifying the dependence of satellite cloud retrievals on instrument uncertainty[J]. Journal of Climate,2017-01-01,30(17)